Lab

Urban Playground Lab

About the lab

Hi, this is Teng Fei, an associate professor in Wuhan University. I am leading this “illegal academic organization”. Here's the link to resume http://faculty.whu.edu.cn/show.jsp?lang=cn&n=Fei%20Teng.

This is a very loosely managed student organization, and it does not even have an ultimate goal. There's only a group of delighted and curious young people use scientific methods to explore freely. I hope even the ravages of the years does NOT limit their imagination.

If you are a student, and feel like you're interested to join in, and if you can come to our biweekly meeting, you may contact me and I will recommend you to our student project leaders. Life is short, let's play more.

生命苦短
赶紧来玩

Featured projects (1)

Project
Remote sensing images at night may miss important profile of population in administrative districts. Then, how about the combination of night-time images from remote sensing and UAV picture?

Featured research (9)

As subjective artistic creations, artistic paintings carry emotion of their creators. Emotions expressed in paintings and emotion aroused in spectators by paintings are two kinds of emotions that scholars have paid attention to. Traditional studies on emotions expressed by paintings are mainly conducted from qualitative perspectives, with neither quantitative output on the emotional values of a painting, nor exploration of trends in the expression of emotion in art history. In this research we threat facial expressions in paintings as an artistic characteristics of art history and employ cognitive computation technology to identify the facial emotions in paintings and to investigate the quantitative measures of paintings from three emotion-related aspects: the spatial and temporal patterns of painting emotions in art history, the gender difference on the emotion of paintings and the color preference associated with emotions. We discovered that the emotion of happiness has a growing trend from ancient to modern times in paintings history, and men and women have different facial expressions patterns along time. As for color preference, artists with different culture backgrounds had similar association preferences between colors and emotions.
Small water bodies have always been an important part of water ecology systems. In the past, due to the limitations of satellite spatial resolution and recognition method precision, there have been few satisfactory remote sensing small water bodies extraction methods. In this article, a method based on index composition and HSI (hue, saturation, and intensity) colour space transformation is proposed to precisely extract small water bodies. An easy-to-deploy, fast, universal, and effective algorithm is used to accurately identify paddy fields and exclude shadows. This method is tested and verified with Sentinel-2 MSI (MultiSpectral Imager) images in seven cities in the Guangdong-Hong Kong-Macao Greater Bay Area. Compared with the traditional modified normalized difference water index (MNDWI) and enhanced water index (EWI) water extraction methods, the proposed HSI method has shown a better performance in small water bodies mapping with a kappa coefficient of 0.94, overall accuracy of 97%, producer’s accuracy of 96%, and user’s accuracy of 98% in test regions, which is significantly higher than the benchmarking water extraction methods. It provides a powerful supplement for the remote sensing monitoring of water resources in surface water bodies. The method proposed in this study exhibits extendibility, it also has the potential to extract other small features with minor modifications of the method.
Various fields have widely used place emotion extracted from social networking sites (SNS) information in recent years. However, the emotional information may contain biases as users are a particular subset of the whole population. This research studies whether there are significant differences between place emotion extracted from SNS and the place in-situ (a campus of Wuhan University). Two datasets from different sources, Weibo (a platform similar to twitter) and in-situ cameras, are collected over the same time periods in the same geographical range. By utilizing online cognitive services on the photos collected, the diversity of people with a recognizable face in terms of age, gender, and emotions are determined. The results suggest that there are significant differences in place emotion extracted from Weibo and in-situ. Furthermore, the pattern of differences varies among diverse demographic groups. This paper quantitatively contrasts place emotion extracted from SNS and the place in-situ, which can help researchers achieve a more profound understanding of human behavior differences between online and offline place emotion. This research also provides a theoretical basis to calibrate the emotion metrics obtained from SNS facial expressions on future place emotion studies.
Various fields have widely used place emotion extracted from social networking sites (SNS) information in recent years. However, the emotional information may contain biases as users are a particular subset of the whole population. This research studies whether there are significant differences between place emotion extracted from SNS and the place in-situ (a campus of Wuhan University). Two datasets from different sources, Weibo (a platform similar to twitter) and in-situ cameras, are collected over the same time periods in the same geographical range. By utilizing online cognitive services on the photos collected, the diversity of people with a recognizable face in terms of age, gender, and emotions are determined. The results suggest that there are significant differences in place emotion extracted from Weibo and in-situ. Furthermore, the pattern of differences varies among diverse demographic groups. This paper quantitatively contrasts place emotion extracted from SNS and the place in-situ, which can help researchers achieve a more profound understanding of human behavior differences between online and offline place emotion. This research also provides a theoretical basis to calibrate the emotion metrics obtained from SNS facial expressions on future place emotion studies.

Lab head

Teng Fei
Department
  • School of Resources and Environmental Science
About Teng Fei
  • Hi, this is Fei Teng.Here's the link to resume http://faculty.whu.edu.cn/show.jsp?lang=cn&n=Fei%20Teng.

Members (17)

Yuhao Kang
  • University of Wisconsin–Madison
Shuangyin Zhang
  • Wuhan University
Jun Li
  • Wuhan University
Siying Wang
  • The University of Hong Kong
Jiaqi Ding
  • Peking University
Hanqi Li
  • Wuhan University
Yingjing Huang
  • Peking University
Yizhuo Li
  • Wuhan University
Meng Bian
Meng Bian
  • Not confirmed yet
Siying Wang
Siying Wang
  • Not confirmed yet
Y. Wang
Y. Wang
  • Not confirmed yet
Yinkang Wan
Yinkang Wan
  • Not confirmed yet
Chen Jia
Chen Jia
  • Not confirmed yet
Kunlin Wu
Kunlin Wu
  • Not confirmed yet
J. Wang
J. Wang
  • Not confirmed yet
yextu.sres@whu.edu.cn
yextu.sres@whu.edu.cn
  • Not confirmed yet

Alumni (1)

Yexin Tu
  • Wuhan University